In this tutorial, learn how to build out seamless connections between Heroku PostgreSQL data and the rest of your analytics infrastructure.
More and more developers are choosing to build their apps on the Heroku platform. Heroku’s fully-managed environment and native integration with PostgreSQL make it a perfect solution for many ISVs. We’ve created a tutorial to help users build out seamless connections between their Heroku Postgres data and the rest of their data and analytics infrastructure.
What is Heroku and Why It Matters
Heroku is a Platform-as-a-Service (PaaS) based on AWS that companies use to develop and launch web applications. Developers increasingly prefer to use Heroku as it is simple to deploy, surprisingly flexible and effortlessly scalable to the needs of the application and business. One main benefit to users is that Heroku completely manages the infrastructure needs of the deployment, leaving the developers free to focus on the app!
PostgreSQL on Heroku
In addition to the fully-managed infrastructure that Heroku provides, developers can also opt for a fully managed Heroku PostgreSQL database deployment. This pairing makes sense given the recent rise in popularity of Postgres. PostgreSQL is open-source, feature-rich, and offers more operating system support options than other similar SQL databases.
Connecting Heroku to PostgreSQL via ODBC/JDBC Connectors
Once you’ve deployed your Heroku + Postgres environment, you’ll more than likely need to connect it to your other cloud and on-prem data sources and apps. Many businesses find that connecting this data in a simple, real-time manner can be difficult or time-consuming. My colleague Saikrishna Bobba has put together a fantastic, step-by-step tutorial to walk you through the process of building this link using Progress DataDirect ODBC and JDBC connectors. This will help you expose your Heroku app data to your BI, CRM, ERP systems and more!
James Goodfellow is Senior Product Marketing Manager at Progress.
Check the tutorial
Or, download a trial driver to get started today:
ODBC TRIAL
JDBC TRIAL
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